Page 224 - Geochemical Anomaly and Mineral Prospectivity Mapping in GIS

226 Chapter 7

Fig. 7-17. (A) An epithermal Au prospectivity map of Aroroy district (Philippines) obtained via
fuzzy logic modeling based on evidential maps with fuzzy evidential scores shown in Table 7-VII
and on the inference network shown in Fig. 7-15. Triangles are locations of known epithermal Au
deposits; whilst polygon outlined in grey is area of stream sediment sample catchment basins (see
Fig. 4-11). (B) Prediction-rate curves of proportion of deposits demarcated by the predictions
versus proportion of study area predicted as prospective. The prediction-rate curve of the map
obtained by using γ=0.5 is compared with prediction-rate curves of map obtained by using γ=0 and
γ=1 in the final step of the inference network in Fig. 7-15. The prediction-rate curves of the maps
obtained by using γ=0.5 and γ=0 mostly overlap each other, meaning that their prediction-rates are
mostly equal. The dots, which pertain to the prediction-rate curve of the map derived by using
γ=0.5, represent classes of prospectivity values that correspond spatially with a number of cross-
validation deposits (indicated in parentheses).

because, if 20% of the case study area is considered prospective, then the former models
delineate correctly seven (or about 58%) of the cross-validation deposits (Figs. 7-16B
and 7-17B) whilst the latter models delineate correctly six (or 50%) of the cross-
validation deposits.
The availability of different fuzzy operators and the ability to modify fuzzy inference
networks is an advantage of fuzzy logic modeling compared to binary and multi-class
index overlay modeling. The advantage of fuzzy logic modeling compared Boolean logic
modeling is mainly in the representation of spatial evidence. However, the assignment of
fuzzy evidential scores is as subjective as the assignment of multi-class index scores. No
two experts will arrive at the same fuzzy prospectivity scores to classes of the same set
of spatial evidence. The disadvantage of fuzzy logic modeling compared to multi-class
index overlay modeling is the presumption of equal weights for individual evidential
maps. The common disadvantage of all these modeling techniques is the implicit
representation of uncertainty of spatial evidence. For example, in fuzzy logic modeling
there is no proper and uniform way of assigning fuzzy prospectivity membership scores